La Trobe separates campus energy measurement from AI-assisted control changes

Ask the campus energy manager, CIO and finance sponsor whether fragmented telemetry prevents them from assessing completed projects. A bounded engagement could reconcile meters and project records for one building before discussing a wider AI purchase. The value hypothesis is traceable evidence for operating decisions. Ask who owns the underlying data and which savings claims finance would accept. This operator account offers a useful discovery example, but does not establish transferable savings, a need for the same supplier or a ready-made opportunity. Smaller campuses may need a simpler measurement service.

Map BMS points, meter identifiers, timestamps and project-change records before selecting a model. Keep the measurement pipeline independently queryable so a controller supplier cannot become the sole source of benefit evidence. For a cloud twin connected to campus operational technology, document network boundaries, credentials, retention and outage behavior. Start with a limited dataset and confirm that displayed values reconcile with source meters. Proposed proof of value should reproduce a preselected building's project comparison and explain missing data; the public account does not establish the platform's security or measurement accuracy.

Make the campus energy manager accountable for measurement definitions and the controls team accountable for approved interventions. Coordinate IT data engineering, commissioning specialists and finance review. Preserve the change log, train operators to investigate anomalies and define who closes each finding. Proposed acceptance requires traceable meter-to-report reconciliation, documented exclusions and a repeatable review by someone outside the implementation team. Accessibility checks should cover the operator dashboard and alarm workflow. Dependencies include instrument calibration and sustained support; risks include attributing mechanical upgrades to AI and losing institutional knowledge when student or project staff rotate.